Tim Cook's Apple put artificial intelligence at the centre of major updates to its iPhone and iPad operating system. Craig Federighi called the update to the operating system the "biggest iOS release ever for our users". One of the biggest themes was artificial intelligence. The Photos app is being updated to scan photos and provide users with more context. Using deep learning the photos app will now scan objects and scenes of photos to build a profile of them and provide images that could be used in the same context.

In the past few years we've seen software giants like Alphabet's Google and Amazon.com Google began as a search bar but now plays in the mobile (Android), media (YouTube), hardware (Motorola), transportation (Waze) and IoT (Nest) spaces as well. Likewise, Amazon.com was originally a site to sell books online, but now sells every product under the sun and operates the world's largest public cloud through Amazon Web Services (AWS). In addition to the behemoths who have aggressively expanded in the past decade, we've witnessed new players barrel in and disrupt additional industries. Airbnb is now valued at 20 Billion – more than every hospitality company in the world except Hilton and Marriott, despite owning no hotels.

Leading global IT services company HCL Technologies has been named winner of the'Best Innovation in Natural Language Processing (NLP)' award at the AIconics Awards during the "AI Summit" in London recently. AIconics are the world's only independently judged awards celebrating the drive, innovation and hard work in the international Artificial Intelligence (AI) community. "This award gives testimony to the innovation and pragmatic implementation of'Natural Language Processing' in the 21st century enterprise," Kalyan Kumar, executive vice president at HCL Technologies, said in a statement. HCL was also named as a finalist in the "Best Intelligent Assistant" category which showcases companies making ground-breaking advancements in virtual assistants and advanced voice/text recognition capabilities. The driving force behind HCL's success at the AIconics Awards is "HCL DryICE" -- the company's innovative autonomics and orchestration framework.

We have been hearing predictions for decades of a takeover of the world by artificial intelligence. In 1957, Herbert A. Simon predicted that within 10 years a digital computer would be the world's chess champion. That didn't happen until 1996. And despite Marvin Minsky's 1970 prediction that "in from three to eight years we will have a machine with the general intelligence of an average human being," we still consider that a feat of science fiction. The pioneers of artificial intelligence were surely off on the timing, but they weren't wrong; AI is coming.

Or to be more specific, they hope to alter your mind with music…music that is composed by an AI (but more on that later). Hewett describes the work as "Auditory brain stimulation," which is a mechanism that relies on something known as "brain entrainment" (also known as "neural entrainment"). This is a novel--and somewhat unconventional--theory that is centered on how brain waves alter in response to acoustic stimulation (sound). The basic idea is that certain sounds evoke very specific responses in the brain. In other words, listening to music can alter, or induce, certain neural oscillations--oscillations that can achieve a host of things, such as altered mood, decreased anxiety, or improved focus. Notably, those who advocate neural entrainment assert that these acoustic-induced alterations can be seen and analyzed via electroencephalogram (EEG) measurements, which is, of course, where the science comes in.

I'm trying to aggregate links and questions that would be useful for people job hunting in ML/data science.

The father of modern speech recognition, Frederick Jelinek, once famously said: 'Anytime a linguist leaves the group, the recognition rate goes up.' Based on this logic, if the domain experts – the phonologists, in his case – were to be exchanged with pure engineers, the performance of the system would improve. Would this theory apply to a system that heavily utilises machine learning? Do the domain experts increase the performance, or is it the lack of them that is best for the system? When working in a highly specialised domain, such as the legal arena, which has clear, well-defined tasks, technology is provided to support, augment and increase productivity. It is often the case that both supervised machine learning techniques (i.e.

Imagine a feedforward network with X input units (i.e. an X-dimensional vector), a hidden layer of Y units, and an output of Z units. Each of the hidden units takes X inputs and produces a single output. Now, imagine that instead of taking just the X inputs from the input layer, each hidden unit also took Y inputs that it produced in the last time step. This is what an RNN layer with Y inputs would be.

Both Amazon and Google are advancing their efforts in machine learning, a type of artificial intelligence that lets computers learn without being explicitly programmed. It's often associated with cloud computing, because it requires the considerable computing power the cloud makes easily available. Amazon's efforts will get a boost when Alexander Smola, a professor in the machine-learning department at Carnegie Mellon University, leaves that position July 1 to head Amazon's cloud machine-learning platform. Smola revealed his plans in this blog post. "This is a terrific task, and it was an offer that I could not turn down," Smola wrote.